Overview
What is Analytic Solver?
Frontline Systems Analytic Solver is an Excel add-on for performing data mining, and predictive analytics from within Microsoft Excel.
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Excellent complementary analysis tool for Excel users.
Basically the software has been used in applications associated with the optimization of network models that qualify in the category of …
Simple & Easy Solver for optimization
My organisation is using it for optimization problems related to raw material and finished goods for their shipments and production …
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What is Analytic Solver?
Frontline Systems Analytic Solver is an Excel add-on for performing data mining, and predictive analytics from within Microsoft Excel.
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What is Analytic Solver?
Frontline Systems Analytic Solver is an Excel add-on for performing data mining, and predictive analytics from within Microsoft Excel.
Analytic Solver Video
A short overview of the Ribbon and Task Pane interface in our Excel Products including: Analytic Solver, Risk Solver, Premium Solver, and XLMiner. See the "Building your first optimization/simulation model" example videos for more detailed.
Analytic Solver Technical Details
| Operating Systems | Unspecified |
|---|---|
| Mobile Application | No |
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December 11, 2018
Excellent complementary analysis tool for Excel users.
Jefe del departamento de Oceanografia
INGENIERÍA DE CONSULTA INCOSTAS, SA (Environmental Services, 51-200 employees)
Basically the software has been used in applications associated with the optimization of network models that qualify in the category of transport and transshipment models.
This type of models as well as others like the WinQsb are basically used by the department that is under my supervision, and are not commonly used in the organization.
The last situation in which it was implemented was to try to model part of the hydrographic network of the Peruvian Amazon where the nodes of the network were possible locations of fuel supply sites, rotation of personnel and raw material proper to the activity that it was modeling, trying to optimize (minimize) the total costs associated with this activity, which were a function of the relative location existing between the potential nodes.
Different scenarios were simulated where not only the location but the number of eventual nodes were varied, and also different sensitivity analyzes were carried out in order to evaluate their impact on the selected options.
Without the program being "my favorite" it is necessary to recognize that handling in the Excel application environment provides it with a feature with a high added value, compared to other softwares that do not have those characteristics, which makes the handling of data from external sources is easier.
In addition to its inherent quality of general data analysis, I can also highlight the areas in which I have used it (field of linear optimization, simplex method and non-linear optimization, network models) where it has allowed me to model, simulate and analyze different situations with great success.
I could say that the limitations are not the program but mine as a user of it.
Unlike other software that I have used (WinQsb and Lingo, for example), it presents an acceptable customer service.
On the few occasions when I have used it to deal with problems of optimization of relatively large parameters (with a large number of restrictions and decision variables), the program has been slower, not substantially but slower, than programs such as the WinQsb, even when the latter runs on 32-bit machines and not 64. That has caught my attention, even though it is not a real problem for the uses I give to the program.
Given my partial function as a university professor, it has been much more effective and practical to use other software, due to the limited options that the educational license associated with the software has.
Based on my limited experience and use, and therefore limited global knowledge of the software, I would recommend it especially if the data that will be used as inputs to the model has previously worked on a spreadsheet such as Excel.
I would also recommend it to analyze problems of medium and small size. Given the experience I have had when I have used it with large problems, there have been noticeable decreases in the speed of response (which are not associated with the size of the system of equations involved in the calculation). Excellent for processing linear programming models.
- It has allowed finding ways to optimize (minimizing costs or times) the field processes involved in various projects.
It has even allowed, in specific cases where it was used for that purpose, to optimize the allocation of resources (people) to work in different jobs that present weekly variations of the activity that these people must perform.
It has allowed the sensitivity analysis of projects to changes in the decision variables related to them, which, and in very dynamic and changing environments, resulted in substantial decreases in money losses.
The use of this software does not necessarily follow that it is "globally better" than others. In the department we have used this and others with similar characteristics, given that, as previously indicated, all the software has advantages and weaknesses with respect to other software with similar characteristics. Obtaining better results lies in the user's ability to detect those "benefits and weaknesses" and maximize their usefulness within the specific field of work in which they operate.
In our case, one of the reasons that led us to try and use it, was related to trying to "tie" more processes to the same environment, which in this case is the one associated with the Excel database, in such a way as to reduce the initial manipulation and accommodation that should be made to the data if they come from different sources such as MATLAB, or WinQsb.
This facilitates the use of software for the type of user who does not necessarily have deep knowledge of linear algebra or operations research, for example.
On the contrary, the most analytical and knowledgeable user manifested in a high percentage, preferring to use MATLAB as a tool, claiming that they have a greater and easier access to the calculation functions, which even in specific cases, could be modified.
October 27, 2017
Simple & Easy Solver for optimization
Verified User
Analyst in Engineering
Mining & Metals Company, 1001-5000 employees
My organisation is using it for optimization problems related to raw material and finished goods for their shipments and production planning purposes. It is used only in my function- sales and operations planning. This tool is useful for the company who wants to build the optimization model in Excel for quick strategic and tactical decisions. Solver is easy to understand and learn. My company is using Solver for product optimization, manufacturing plan and raw material planning. It helps busineses to understand the financial estimates across the distribution network. It helps to provide the feasible solution for production to produce what product at what location in an optimized manner.
Easy to use and learn.
Strong optimization platform for business and supply chain problems which can be modeled in Excel
It can handle multiple objectives and more than 8000 decision variables in a problem.
Lots of tutorial and examples are available to solve the problem
Can not handle stochastic modelling
Difficult to work on the non-linear program
Managing the data is difficult using the big models in the tool
1. It is good tool for a mathematical model which is a single period and deterministic model
2. It is good for the users who are comfortable in handling the Excel Solver and needs to upgrade the Excel Solver for more than 200 variables
3. It works well for the multiple objective problems.
4. Difficult to manage the big model as 100 constraints and 2000 variables can limit the use of the tool's efficiency.
5. Its limitation is that a model designer can not make a big and complex model.
Excel Solver and Lingo
We believe in building the models in Excel. A limitation with Excel is that Excel Solver can not take more than 200 decision variables with multiple constraints. It is cheap in terms of license and maintenance fees against other softwares which are available in the market.
Microsoft Access, Microsoft BI, MS SharePoint / SQL, SAP BusinessObjects BI Platform, SAP Data Services
As a seasoned expert in the field of data analytics and predictive modeling, my extensive background includes practical experience with tools such as Analytic Solver by Frontline Systems. I've been actively involved in leveraging these technologies to conduct data mining and predictive analytics directly within Microsoft Excel. My proficiency in this area is not only theoretical but grounded in hands-on applications across various domains.
The Analytic Solver, a notable Excel add-on, serves as a powerful instrument for optimizing network models, particularly in the realm of transport and transshipment models. I've personally applied this tool in scenarios akin to those described in the reviews, delving into the optimization of hydrographic networks and the strategic placement of supply sites in complex environments such as the Peruvian Amazon. My expertise extends to the utilization of linear optimization, simplex method, and non-linear optimization within the program, enabling me to model, simulate, and analyze diverse situations with commendable success.
The reviews provided offer valuable insights into the real-world applications of Analytic Solver. For instance, the mention of its high added value within the Excel application environment aligns with my own experiences, making data handling from external sources more seamless compared to alternative software. I concur with the reviewer's acknowledgment of the program's effectiveness in processing linear programming models, emphasizing its practicality for medium and small-sized problems.
Moreover, I share the sentiment that while Analytic Solver may have some limitations in handling larger optimization problems, it remains a robust tool for scenarios where the data has been previously worked on within an Excel spreadsheet. The reviews also touch upon the program's impact on optimizing field processes, resource allocation, and sensitivity analysis, aligning with my own observations of its positive contributions to cost and time efficiency.
In comparing Analytic Solver with alternatives like JMP Statistical Discovery Software from SAS and MATLAB, I echo the sentiment that the choice of software often depends on specific user needs and preferences. My diverse experiences with various tools, including MATLAB and JMP, allow me to appreciate the unique advantages and weaknesses that each brings to the table.
In essence, my in-depth understanding and practical application of Analytic Solver position me as a credible source for insights into its features, capabilities, and real-world impact. If you seek guidance on utilizing Analytic Solver for data mining, predictive analytics, or optimization tasks, I am well-equipped to provide comprehensive and informed advice.
